Modeling atmospheric chemistry and transport with dynamic adaptive resolution |
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| Authors: | Emil M Constantinescu Adrian Sandu Gregory R Carmichael |
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| Institution: | (1) Department of Computer Science, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA;(2) Center for Global and Regional Environmental Research, University of Iowa, 204 IATL, Iowa City, IA, USA |
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| Abstract: | We discuss an adaptive resolution system for modeling regional air pollution based on the chemical transport model STEM. The
grid adaptivity is implemented using the generic adaptive mesh refinement tool Paramesh, which enables the grid management
operations while harnessing the power of parallel computers. The computational algorithm is based on a decomposition of the
domain, with the solution in different subdomains being computed with different spatial resolutions. Various refinement criteria
that adaptively control the fine grid placement are analyzed to maximize the solution accuracy while maintaining an acceptable
computational cost. Numerical experiments in a large-scale parallel setting (~0.5 billion variables) confirm that adaptive
resolution, based on a well-chosen refinement criterion, leads to the decrease in spatial error with an acceptable increase
in computational time. Fully dynamic grid adaptivity for air quality models is relatively new. We extend previous work on
chemical and transport modeling by using dynamically adaptive grid resolution. Advantages and shortcomings of the present
approach are also discussed. |
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| Keywords: | Air pollution modeling Adaptive mesh refinement Chemical and transport models |
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